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Creative design inspired by biological knowledge: Technologies and methods

Runhua TAN, Wei LIU, Guozhong CAO, Yuan SHI

《机械工程前沿（英文）》 2019年 第14卷 第1期   页码 1-14 doi: 10.1007/s11465-018-0511-0

摘要： Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

关键词： creative design     biologically inspired methods     key technologies    

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情境感知智能产品的生物启发式设计 Article

Ang Liu, Ivan Teo, 陈点滴, Stephen Lu, Thorsten Wuest, 张执南, 陶飞

《工程（英文）》 2019年 第5卷 第4期   页码 637-645 doi: 10.1016/j.eng.2019.06.005

摘要：

信息通信技术（ICT）和网络物理系统（CPS）的快速发展，为智能产品的日益普及铺平了道路。情境感知是衡量产品智能的一个重要角度。与人工制品不同，各种生物系统具有非凡的情境感知能力。生物启发式设计（BID）是最常用的设计策略之一。然而，迄今为止，很少有研究检查过情境感知智能产品的生物启发式设计。本文提出了一个结构化设计框架，用以支持情境感知智能产品的生物启发式设计。本文从产品设计的角度定义了情境感知的概念。该框架以功能-行为-结构理论（the situated function-behavior-structure ontology）为基础开发而成。本文规定了结构化设计过程，借助各种生物启发，支持不同的概念设计活动，如问题形成、结构重构、行为重构和功能重构。一些现有的设计方法和新兴的设计工具被纳入框架。本文提出了一个案例研究，展示了如何利用该框架重新设计机器人吸尘器，使其更具有情境感知能力。

关键词： 设计方法     生物启发式设计     情境感知     智能设计    

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Biologically inspired model of path integration based on head direction cells and grid cells

Yang ZHOU,De-wei WU

《信息与电子工程前沿（英文）》 2016年 第17卷 第5期   页码 435-448 doi: 10.1631/FITEE.1500364

摘要： Some neurons in the brain of freely moving rodents show special firing pattern. The firing of head direction cells (HDCs) and grid cells (GCs) is related to the moving direction and distance, respectively. Thus, it is considered that these cells play an important role in the rodents’ path integration. To provide a bionic approach for the vehicle to achieve path integration, we present a biologically inspired model of path integration based on the firing characteristics of HDCs and GCs. The detailed implementation process of this model is discussed. Besides, the proposed model is realized by simulation, and the path integration performance is analyzed under different conditions. Simulations validate that the proposed model is effective and stable.

关键词： Head direction cells (HDCs)     Grid cells (GCs)     Path integration     Bionic navigation    

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Influence of pore structure on biologically activated carbon performance and biofilm microbial characteristics

《环境科学与工程前沿（英文）》 2021年 第15卷 第6期 doi: 10.1007/s11783-021-1419-1

摘要：

• Pore structure affects biologically activated carbon performance.

关键词： Granular activated carbon     Biologically activated carbon filter     Bacterial community structure     Pore structure    

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Evaluate HAA removal in biologically active carbon filters using the ICR database

Hsin-hsin TUNG, Yuefeng F. XIE

《环境科学与工程前沿（英文）》 2011年 第5卷 第4期   页码 489-496 doi: 10.1007/s11783-011-0312-8

摘要： The effects of biologically active carbon (BAC) filtration on haloacetic acid (HAA) levels in plant effluents and distribution systems were investigated using the United States Environmental Protection Agency’s Information Collection Rule (ICR) database. The results showed that average HAA5 concentrations in all locations were 20.4 μg·L and 29.6 μg·L in ICR plants with granular activated carbon (GAC) and ICR plants without GAC process, respectively. For plants without GAC, the highest HAA levels were observed in the quarters of April to June and July to September. However, for plants with GAC, the highest HAA levels were observed in the quarters of April to June and January to March. This HAA level profile inversely correlated well with water temperature, or biologic activity. For GAC plants, simulated distribution samples matched well with distribution system equivalent samples for Cl AA and THMs. For plants with and without GAC, simulated distribution samples overestimated readily biodegradable HAAs in distribution systems. The study indicated that through HAA biodegradation, GAC process plays an important role in lowering HAA levels in finished drinking water.

关键词： biologically active carbon (BAC)     disinfection byproduct (DBP)     granular activated carbon (GAC)     haloacetic acid (HAA)     Information Collection Rule (ICR)    

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Effect of loading rate on shear strength parameters of mechanically and biologically treated waste

《环境科学与工程前沿（英文）》 2022年 第16卷 第12期 doi: 10.1007/s11783-022-1595-7

摘要：

● Mechanical behavior of MBT waste affected by loading rate was investigated.

关键词： Mechanically and biologically treated waste     Landfill     Triaxial test     Loading rate     Axial strain     Shear strength parameter    

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Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

《能源前沿（英文）》 2014年 第8卷 第2期   页码 254-260 doi: 10.1007/s11708-014-0302-1

摘要： The application of a quantum-inspired firefly algorithm was introduced to obtain optimal power quality monitor placement in a power system. The conventional binary firefly algorithm was modified by using quantum principles to attain a faster convergence rate that can improve system performance and to avoid premature convergence. In the optimization process, a multi-objective function was used with the system observability constraint, which is determined via the topological monitor reach area concept. The multi-objective function comprises three functions: number of required monitors, monitor overlapping index, and sag severity index. The effectiveness of the proposed method was verified by applying the algorithm to an IEEE 118-bus transmission system and by comparing the algorithm with others of its kind.

关键词： quantum-inspired binary firefly algorithm     topological monitor reach area     power quality    

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

《结构与土木工程前沿（英文）》 2021年 第15卷 第3期   页码 665-681 doi: 10.1007/s11709-021-0713-0

摘要： The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (Rtest = 0.923) and minimum root mean square error value (RMSEtest = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

关键词： long contraction scour     prediction     uncertainty     ANFIS model     meta-heuristic algorithm    

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Surgical robotics: A look-back of latest advancement and bio-inspired ways to tackle existing challenges

Yang LIU, Jing LIU

《机械工程前沿（英文）》 2012年 第7卷 第4期   页码 376-384 doi: 10.1007/s11465-012-0352-1

摘要：

This article is dedicated to present a review on existing challenges and latest developments in surgical robotics in attempts to overcome the obstacles lying behind. Rather than to perform an exhaustive evaluation, we would emphasize more on the new insight by digesting the emerging bio-inspired surgical technologies with potentials to revolutionize the field. Typical approaches, possible applications, advantages and technical challenges were discussed. Evolutions of surgical robotics and future trends were analyzed. It can be found that, the major difficulties in the field of surgical robots may not be properly addressed by only using conventional approaches. As an alternative, bio-inspired methods or materials may shed light on new innovations. While endeavors to deal with existing strategies still need to be made, attentions should be paid to also borrow ideas from nature.

关键词： minimally invasive surgery     surgical robotics     haptic feedback     miniaturization     bio-inspiration     bionics    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

《机械工程前沿（英文）》 2021年 第16卷 第4期   页码 814-828 doi: 10.1007/s11465-021-0650-6

摘要： The fault diagnosis of bearings is crucial in ensuring the reliability of rotating machinery. Deep neural networks have provided unprecedented opportunities to condition monitoring from a new perspective due to the powerful ability in learning fault-related knowledge. However, the inexplicability and low generalization ability of fault diagnosis models still bar them from the application. To address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings. The proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision tree methods by rebuilding the output decision layer of CNN according to the hierarchical structural characteristics of the decision tree, which is by no means a simple combination of the two models. The proposed DCTN model has unique advantages in 1) the hierarchical structure that can support more accuracy and comprehensive fault diagnosis, 2) the better interpretability of the model output with hierarchical decision making, and 3) more powerful generalization capabilities for the samples across fault severities. The multiclass fault diagnosis case and cross-severity fault diagnosis case are executed on a multicondition aeronautical bearing test rig. Experimental results can fully demonstrate the feasibility and superiority of the proposed method.

关键词： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network     decision tree    

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concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

《结构与土木工程前沿（英文）》 2021年 第15卷 第1期   页码 61-79 doi: 10.1007/s11709-020-0684-6

摘要： Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C–O, C–W, C–F, O–W, O–F, and W–F), trivariate (C–O–W, C–W–F, O–W–F), and four-variate (C–O–W–F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS–DE– (O) (MP= 0.96), ANFIS–PSO– (C-O) (MP= 0.88), ANFIS–DE– (O–W–F) (MP= 0.94), and ANFIS–PSO– (C–O–W–F) (MP= 0.89), respectively. ANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

关键词： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive strength    

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Thermo-fluidic devices and materials inspired from mass and energy transport phenomena in biological

Jian XIAO , Jing LIU ,

《能源前沿（英文）》 2009年 第3卷 第1期   页码 47-59 doi: 10.1007/s11708-008-0068-4

摘要： Mass and energy transport consists of one of the most significant physiological processes in nature, which guarantees many amazing biological phenomena and activities. Borrowing such idea, many state-of-the-art thermo-fluidic devices and materials such as artificial kidneys, carrier erythrocyte, blood substitutes and so on have been successfully invented. Besides, new emerging technologies are still being developed. This paper is dedicated to presenting a relatively complete review of the typical devices and materials in clinical use inspired by biological mass and energy transport mechanisms. Particularly, these artificial thermo-fluidic devices and materials will be categorized into organ transplantation, drug delivery, nutrient transport, micro operation, and power supply. Potential approaches for innovating conventional technologies were discussed, corresponding biological phenomena and physical mechanisms were interpreted, future promising mass-and-energy-transport-based bionic devices were suggested, and prospects along this direction were pointed out. It is expected that many artificial devices based on biological mass and energy transport principle will appear to better improve various fields related to human life in the near future.

关键词： bionics     mass transport     energy transport     artificial devices and materials     biology system     nature phenomena     medical device.    

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Biomineralization-inspired copper-cystine nanoleaves capable of laccase-like catalysis for the colorimetric

Miao Guan, Mengfan Wang, Wei Qi, Rongxin Su, Zhimin He

《化学科学与工程前沿（英文）》 2021年 第15卷 第2期   页码 310-318 doi: 10.1007/s11705-020-1940-y

摘要： Recently, many efforts have been dedicated to creating enzyme-mimicking catalysts to replace natural enzymes in practical fields. Inspired by the pathological biomineralization behaviour of L-cystine, in this study, we constructed a laccase-like catalyst through the co-assembly of L-cystine with Cu ions. Structural analysis revealed that the formed catalytic Cu-cystine nanoleaves (Cu-Cys NLs) possess a Cu(I)-Cu(II) electron transfer system similar to that in natural laccase. Reaction kinetic studies demonstrated that the catalyst follows the typical Michaelis-Menten model. Compared with natural laccase, the Cu-Cys NLs exhibit superior stability during long-term incubation under extreme pH, high-temperature or high-salt conditions. Remarkably, the Cu-Cys NLs could be easily recovered and still maintained 76% of their activity after 8 cycles. Finally, this laccase mimic was employed to develop a colorimetric method for epinephrine detection, which achieved a wider linear range (9–455 μmol·L ) and lower limit of detection (2.7 μmol·L ). The Cu-Cys NLs also displayed excellent specificity and sensitivity towards epinephrine in a test based on urine samples.

关键词： biomineralization     laccase     L-cystine     colorimetric detection     enzyme mimic    

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A review of optimization modeling and solution methods in renewable energy systems

《工程管理前沿（英文）》   页码 640-671 doi: 10.1007/s42524-023-0271-3

摘要： The advancement of renewable energy (RE) represents a pivotal strategy in mitigating climate change and advancing energy transition efforts. A current of research pertains to strategies for fostering RE growth. Among the frequently proposed approaches, employing optimization models to facilitate decision-making stands out prominently. Drawing from an extensive dataset comprising 32806 literature entries encompassing the optimization of renewable energy systems (RES) from 1990 to 2023 within the Web of Science database, this study reviews the decision-making optimization problems, models, and solution methods thereof throughout the renewable energy development and utilization chain (REDUC) process. This review also endeavors to structure and assess the contextual landscape of RES optimization modeling research. As evidenced by the literature review, optimization modeling effectively resolves decision-making predicaments spanning RE investment, construction, operation and maintenance, and scheduling. Predominantly, a hybrid model that combines prediction, optimization, simulation, and assessment methodologies emerges as the favored approach for optimizing RES-related decisions. The primary framework prevalent in extant research solutions entails the dissection and linearization of established models, in combination with hybrid analytical strategies and artificial intelligence algorithms. Noteworthy advancements within modeling encompass domains such as uncertainty, multienergy carrier considerations, and the refinement of spatiotemporal resolution. In the realm of algorithmic solutions for RES optimization models, a pronounced focus is anticipated on the convergence of analytical techniques with artificial intelligence-driven optimization. Furthermore, this study serves to facilitate a comprehensive understanding of research trajectories and existing gaps, expediting the identification of pertinent optimization models conducive to enhancing the efficiency of REDUC development endeavors.

关键词： renewable energy system     bibliometrics     mathematical programming     optimization models     solution methods    

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Intelligent methods for the process parameter determination of plastic injection molding

Huang GAO, Yun ZHANG, Xundao ZHOU, Dequn LI

《机械工程前沿（英文）》 2018年 第13卷 第1期   页码 85-95 doi: 10.1007/s11465-018-0491-0

摘要：

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system-based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

关键词： injection molding     intelligent methods     process parameters     optimization    

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标题 作者 时间 类型 操作

Creative design inspired by biological knowledge: Technologies and methods

Runhua TAN, Wei LIU, Guozhong CAO, Yuan SHI

期刊论文

情境感知智能产品的生物启发式设计

Ang Liu, Ivan Teo, 陈点滴, Stephen Lu, Thorsten Wuest, 张执南, 陶飞

期刊论文

Biologically inspired model of path integration based on head direction cells and grid cells

Yang ZHOU,De-wei WU

期刊论文

Influence of pore structure on biologically activated carbon performance and biofilm microbial characteristics

期刊论文

Evaluate HAA removal in biologically active carbon filters using the ICR database

Hsin-hsin TUNG, Yuefeng F. XIE

期刊论文

Effect of loading rate on shear strength parameters of mechanically and biologically treated waste

期刊论文

Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

期刊论文

Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

期刊论文

Surgical robotics: A look-back of latest advancement and bio-inspired ways to tackle existing challenges

Yang LIU, Jing LIU

期刊论文

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

期刊论文

concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspired

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

期刊论文

Thermo-fluidic devices and materials inspired from mass and energy transport phenomena in biological

Jian XIAO , Jing LIU ,

期刊论文

Biomineralization-inspired copper-cystine nanoleaves capable of laccase-like catalysis for the colorimetric

Miao Guan, Mengfan Wang, Wei Qi, Rongxin Su, Zhimin He

期刊论文

A review of optimization modeling and solution methods in renewable energy systems

期刊论文

Intelligent methods for the process parameter determination of plastic injection molding

Huang GAO, Yun ZHANG, Xundao ZHOU, Dequn LI

期刊论文